With the holidays well behind us, it’s time to take stock of 2018 and discuss what’s ahead for 2019 and beyond. In the past few years, advanced analytics has become much more accessible for many non-tech companies, driven by cheaper storage and improved processing power. Healthcare and the life sciences industries, in particular, are now seeing a lot of interest in the growing volumes of healthcare data, along with increased demand in outcomes-based product design and commercialization from regulators, customers and communities.

Today, when we think of advanced analytics, we think of AI solutions like self-driving cars, automated personal assistants or cancer diagnoses by image recognition. But when many medtech leaders go to work, all they see is reports. For commercial leaders and field managers, “analytics” is limited to slicing and dicing some data, at times with better visualizations and dashboards. Medtech needs to up its analytics game, but what does that entail?

When speaking with clients and colleagues about the promise of advanced analytics for medical device companies, I often hear that there’s not enough good data for analytics, or that internal data is patchy, incomplete, poorly defined and spread across many systems. Those with pharmaceutical experience complain of the lack of market data, such as physician-level prescription data sets used by pharma companies, which would allow medtech companies to have visibility into their own market share, along with full product usage and potential of their customers.

With the holidays well behind us, it’s time to take stock of 2018 and discuss what’s ahead for 2019 and beyond. In the past few years, advanced analytics has become much more accessible for many non-tech companies, driven by cheaper storage and improved processing power. Healthcare and the life sciences industries, in particular, are now seeing a lot of interest in the growing volumes of healthcare data, along with increased demand in outcomes-based product design and commercialization from regulators, customers and communities.

Today, when we think of advanced analytics, we think of AI solutions like self-driving cars, automated personal assistants or cancer diagnoses by image recognition. But when many medtech leaders go to work, all they see is reports. For commercial leaders and field managers, “analytics” is limited to slicing and dicing some data, at times with better visualizations and dashboards. Medtech needs to up its analytics game, but what does that entail?

When speaking with clients and colleagues about the promise of advanced analytics for medical device companies, I often hear that there’s not enough good data for analytics, or that internal data is patchy, incomplete, poorly defined and spread across many systems. Those with pharmaceutical experience complain of the lack of market data, such as physician-level prescription data sets used by pharma companies, which would allow medtech companies to have visibility into their own market share, along with full product usage and potential of their customers.